3 Modeling Example: specific person, company, event, plantA database can be modeled as:a collection of entities,relationship among entities.An entity is an object that exists and is distinguishable from other objects.Example: specific person, company, event, plantEntities have attributesExample: people have names and addressesAn entity set is a set of entities of the same type that share the same properties.Example: set of all persons, companies, trees, holidays

7 Relationship Sets (Cont.)An attribute can also be property of a relationship set.For instance, the depositor relationship set between entity sets customer and account may have the attribute access-date

8 Degree of a Relationship SetRefers to number of entity sets that participate in a relationship set.Relationship sets that involve two entity sets are binary (or degree two). Generally, most relationship sets in a database system are binary.Relationship sets may involve more than two entity sets.Relationships between more than two entity sets are rare. Most relationships are binary. (More on this later.)Example: Suppose employees of a bank may have jobs (responsibilities) at multiple branches, with different jobs at different branches. Then there is a ternary relationship set between entity sets employee, job, and branch

9 AttributesAn entity is represented by a set of attributes, that is descriptive properties possessed by all members of an entity set.Domain – the set of permitted values for each attributeAttribute types:Simple and composite attributes.Single-valued and multi-valued attributesExample: multivalued attribute: phone_numbersDerived attributesCan be computed from other attributesExample: age, given date_of_birthExample:customer = (customer_id, customer_name, customer_street, customer_city ) loan = (loan_number, amount )

11 Mapping Cardinality ConstraintsExpress the number of entities to which another entity can be associated via a relationship set.Most useful in describing binary relationship sets.For a binary relationship set the mapping cardinality must be one of the following types:One to oneOne to manyMany to oneMany to many

12 Mapping CardinalitiesOne to oneOne to manyNote: Some elements in A and B may not be mapped to anyelements in the other set

13 Mapping CardinalitiesMany to oneMany to manyNote: Some elements in A and B may not be mapped to anyelements in the other set

14 KeysA super key of an entity set is a set of one or more attributes whose values uniquely determine each entity.A candidate key of an entity set is a minimal super keyCustomer_id is candidate key of customeraccount_number is candidate key of accountAlthough several candidate keys may exist, one of the candidate keys is selected to be the primary key.

15 Keys for Relationship SetsThe combination of primary keys of the participating entity sets forms a super key of a relationship set.(customer_id, account_number) is the super key of depositor

19 Roles Entity sets of a relationship need not be distinctThe labels “manager” and “worker” are called roles; they specify how employee entities interact via the works_for relationship set.Roles are indicated in E-R diagrams by labeling the lines that connect diamonds to rectangles.Role labels are optional, and are used to clarify semantics of the relationship

20 Cardinality ConstraintsWe express cardinality constraints by drawing either a directed line (), signifying “one,” or an undirected line (—), signifying “many,” between the relationship set and the entity set.One-to-one relationship:A customer is associated with at most one loan via the relationship borrowerA loan is associated with at most one customer via borrower

21 One-To-Many RelationshipIn the one-to-many relationship a loan is associated with at most one customer via borrower, a customer is associated with several (including 0) loans via borrower

22 Many-To-One RelationshipsIn a many-to-one relationship a loan is associated with several (including 0) customers via borrower, a customer is associated with at most one loan via borrower

24 Participation of an Entity Set in a Relationship SetTotal participation (indicated by double line): every entity in the entity set participates in at least one relationship in the relationship setE.g. participation of loan in borrower is totalevery loan must have a customer associated to it via borrowerPartial participation: some entities may not participate in any relationship in the relationship setExample: participation of customer in borrower is partial

26 Design IssuesUse of entity sets vs. attributes Choice mainly depends on the structure of the enterprise being modeled, and on the semantics associated with the attribute in question.Use of entity sets vs. relationship sets Possible guideline is to designate a relationship set to describe an action that occurs between entitiesBinary versus n-ary relationship sets Although it is possible to replace any nonbinary (n-ary, for n > 2) relationship set by a number of distinct binary relationship sets, a n-ary relationship set shows more clearly that several entities participate in a single relationship.

27 Existence DependenciesIf the existence of entity x depends on the existence of entity y, then x is said to be existence dependent on y.y is a dominant entity (in example below, loan)x is a subordinate entity (in example below, payment)loan-paymentpaymentloanIf a loan entity is deleted, then all its associated payment entities must be deleted also.

28 Weak Entity SetsAn entity set that does not have a primary key is referred to as a weak entity set.The existence of a weak entity set depends on the existence of a identifying entity setit must relate to the identifying entity set via a total, one-to-many relationship set from the identifying to the weak entity setIdentifying relationship depicted using a double diamondThe discriminator (or partial key) of a weak entity set is the set of attributes that distinguishes among all the entities of a weak entity set.The primary key of a weak entity set is formed by the primary key of the strong entity set on which the weak entity set is existence dependent, plus the weak entity set’s discriminator.

29 Weak Entity Sets (Cont.)We depict a weak entity set by double rectangles.We underline the discriminator of a weak entity set with a dashed line.payment_number – discriminator of the payment entity setPrimary key for payment – (loan_number, payment_number)

30 Extended E-R Features: SpecializationTop-down design process; we designate subgroupings within an entity set that are distinctive from other entities in the set.These subgroupings become lower-level entity sets that have attributes or participate in relationships that do not apply to the higher-level entity set.Depicted by a triangle component labeled ISA (E.g. customer “is a” person).Attribute inheritance – a lower-level entity set inherits all the attributes and relationship participation of the higher-level entity set to which it is linked.

32 Extended ER Features: GeneralizationA bottom-up design process – combine a number of entity sets that share the same features into a higher-level entity set.Specialization and generalization are simple inversions of each other; they are represented in an E-R diagram in the same way.The terms specialization and generalization are used interchangeably.

33 AggregationConsider the ternary relationship works_on, which we saw earlierSuppose we want to record managers for tasks performed by an employee at a branch

34 Aggregation (Cont.)Relationship sets works_on and manages represent overlapping informationEvery manages relationship corresponds to a works_on relationshipHowever, some works_on relationships may not correspond to any manages relationshipsSo we can’t discard the works_on relationshipEliminate this redundancy via aggregationTreat relationship as an abstract entityAllows relationships between relationshipsAbstraction of relationship into new entityWithout introducing redundancy, the following diagram represents:An employee works on a particular job at a particular branchAn employee, branch, job combination may have an associated manager

36 E-R Design DecisionsThe use of an attribute or entity set to represent an object.Whether a real-world concept is best expressed by an entity set or a relationship set.The use of a ternary relationship versus a pair of binary relationships.The use of a strong or weak entity set.The use of specialization/generalization – contributes to modularity in the design.The use of aggregation – can treat the aggregate entity set as a single unit without concern for the details of its internal structure.

38 Reduction to Relation SchemasPrimary keys allow entity sets and relationship sets to be expressed uniformly as relation schemas that represent the contents of the database.A database which conforms to an E-R diagram can be represented by a collection of schemas.For each entity set and relationship set there is a unique schema that is assigned the name of the corresponding entity set or relationship set.Each schema has a number of columns (generally corresponding to attributes), which have unique names.

39 Representing Entity Sets as SchemasA strong entity set reduces to a schema with the same attributes.A weak entity set becomes a table that includes a column for the primary key of the identifying strong entity setpayment =( loan_number, payment_number, payment_date, payment_amount )

40 Representing Relationship Sets as SchemasA many-to-many relationship set is represented as a schema with attributes for the primary keys of the two participating entity sets, and any descriptive attributes of the relationship set.Example: schema for relationship set borrowerborrower = (customer_id, loan_number )

41 Redundancy of SchemasMany-to-one and one-to-many relationship sets that are total on the many-side can be represented by adding an extra attribute to the “many” side, containing the primary key of the “one” sideExample: Instead of creating a schema for relationship set account_branch, add an attribute branch_name to the schema arising from entity set account

42 Redundancy of Schemas (Cont.)The schema corresponding to a relationship set linking a weak entity set to its identifying strong entity set is redundant.Example: The payment schema already contains the attributes that would appear in the loan_payment schema (i.e., loan_number and payment_number).

43 Composite and Multivalued AttributesComposite attributes are flattened out by creating a separate attribute for each component attributeExample: given entity set customer with composite attribute name with component attributes first_name and last_name the schema corresponding to the entity set has two attributes name.first_name and name.last_nameA multivalued attribute M of an entity E is represented by a separate schema EMSchema EM has attributes corresponding to the primary key of E and an attribute corresponding to multivalued attribute MExample: Multivalued attribute dependent_names of employee is represented by a schema: employee_dependent_names = ( employee_id, dname)Each value of the multivalued attribute maps to a separate tuple of the relation on schema EMFor example, an employee entity with primary key and dependents Jack and Jane maps to two tuples: ( , Jack) and ( , Jane)

44 Representing Specialization via SchemasMethod 1:Form a schema for the higher-level entityForm a schema for each lower-level entity set, include primary key of higher-level entity set and local attributes schema attributes person name, street, city customer name, credit_rating employee name, salaryDrawback: getting information about, an employee requires accessing two relations, the one corresponding to the low-level schema and the one corresponding to the high-level schema

45 Representing Specialization as Schemas (Cont.)Method 2:Form a schema for each entity set with all local and inherited attributesschema attributes person name, street, city customer name, street, city, credit_rating employee name, street, city, salaryDrawback: street and city may be stored redundantly for people who are both customers and employees